Service providers and device manufacturers (e.g., wireless, cellular, etc.) are continually challenged to deliver value and convenience to consumers by, for example, providing compelling network services. One area of interest has been the development of predictive traffic applications (e.g. traffic speed, traffic volume, etc.) as a means of conveying real-time information to travelers. However, when displaying mapping and/or navigation information for users, there may be discrepancies between predicted traffic (historical models) and actual traffic. This problem may be particularly acute for users traveling on a road including unconventional traffic patterns, such as may be due to multiple factors that affect traffic (e.g. weather, seasonality, time of day, week, month, etc.) and making traffic prediction adjustments in real-time. Accordingly, service providers and developers face significant technical challenges in adjusting to traffic variability in real-time for predictive models in mapping and/or navigation applications.